Team Leader - Engineering

Company: Easy Clinic

Location: Kolkata, India (on-site; relocation supported)

Reports to: Founder and CEO

Team: Will lead a newly created pod of 4 to 6 engineers with strong emphasis on AI first development

Level: Senior individual contributor with team leadership

ABOUT EASY CLINIC

Easy Clinic is a healthcare ERP and EMR platform used by 5,000 plus providers across 18 countries, primarily India, Africa and Southeast Asia. Our customers are clinics, clinic chains, nursing homes and hospital OPDs. The platform covers Patient Records and EMR, OPD, IPD and ADT, Pharmacy, Lab, Inventory, Billing and Finance, Appointments and CuraPilot, our AI clinical copilot.

This is not a single-market product. We want a energetic codebase that has to satisfy regulatory requirements across clients in SE Asia, Africa & India. That constraint shapes every engineering decision we make.

WHY THIS ROLE EXISTS

We have a product with real scale and real complexity, and we need a hands-on engineering leader in Kolkata who can own delivery end to end: architecture, code quality, release discipline, and the growth of the team.

We are hiring for the person, not the title. This is a senior seat with real scope from the start, and the scope grows with what you demonstrate.

AI-FIRST IS NOT OPTIONAL HERE

Read this section carefully. If it does not describe how you already work, this is not the right role.

AI in the product. CuraPilot, our clinical copilot, is central to where Easy Clinic is going. We are not adding a chatbot to an existing product. We are rebuilding how clinicians and clinic operators interact with the system. Our design philosophy is automation-heavy over AI-heavy: rules engines and database queries run before any model call, and every AI feature is designed against a strict per-visit cost ceiling. We expect you to think in those terms from day one, which means understanding token economics, prompt design, context management, latency budgets, evaluation and failure modes, and knowing when a deterministic rule beats a model call.

AI in how we build. We expect the engineering team to use AI tooling seriously in daily work: code generation, review, test authoring, migration and documentation. A team leader who does not use these tools well will slow down engineers who do. We want someone who has opinions on where AI-assisted development helps, where it produces liabilities, and how to set review standards so that quality holds as output volume increases.

AI in what you propose. The strongest candidate will look at our modules and immediately see where intelligence should sit: triage, coding and claims, inventory forecasting, recall and no-show prediction, revenue leakage detection. We want that instinct, backed by the judgement to say when the answer is a well-designed query rather than a model.

WHAT YOU WILL OWN

Technical

- Architecture and design decisions across a multi-tenant .NET and Angular platform
- Hands-on coding: you will write and review production code every week, not supervise from a distance




- Code review standards, branching strategy, CI/CD pipeline, release management
- Performance, scalability and data integrity across large multi-tenant SQL Server workloads
- Technical debt strategy: knowing what to fix, what to isolate, and what to leave alone
- Integration architecture for payer systems, government health APIs, lab and pharmacy equipment, and AI services

Product and delivery

- Translating product intent into technical scope, then holding the line on what actually ships
- Sequencing work so that platform improvements and customer-driven features move together
- Estimating honestly and defending estimates with reasoning
- Owning quality: production defects in a clinical system are not acceptable as a normal cost of shipping

Team

- Building and leading a newly created pod of 4 to 6 engineers
- Hiring, onboarding and raising the technical bar of the team
- Building engineering practices that survive without constant supervision

WHO WE ARE LOOKING FOR

Product engineering background, not services or projects

This is the single most important filter. We are looking for someone who has built and evolved a product over multiple years and multiple releases, where the same codebase kept getting better. If your experience is a sequence of client projects that were delivered and handed over, this role will not fit.

Concretely, we expect you to have:

- Owned a product or a major product module through several release cycles
- Lived with the consequences of your own architecture decisions over 2 plus years
- Made deliberate trade-offs between customer-specific requests and platform generality
- Experience with versioning, backward compatibility and migration of live customer data
- A view on what should be configurable versus what should be coded

Experience

- 8 to 12 years in software engineering, with at least 3 years leading a team
- Deep, current, hands-on .NET expertise: C#, ASP.NET Core, Entity Framework Core, REST API design
- Strong Angular experience: components, RxJS, state management, performance in large applications
- Strong SQL Server: schema design, query optimisation, indexing, stored procedures, execution plan analysis
- Multi-tenant SaaS architecture: tenant isolation, configuration layering, per-tenant customisation without codebase forking
- Cloud deployment on Azure: App Services, SQL, storage, monitoring, cost awareness
- Git, CI/CD, automated testing
- Demonstrated experience shipping LLM or AI features into production, including prompt and context design, cost control, latency management, and handling non-deterministic output safely
- Active daily use of AI development tooling,



with a considered view on where it helps and where it creates risk

Highly valued

- Healthcare software experience: EMR, HMS, LIS, PACS, claims or insurance systems
- Interoperability standards: HL7, FHIR, DICOM
- Regulatory and compliance-driven development: data residency, audit trails, consent, role-based access
- Retrieval architectures, structured output, evaluation harnesses and guardrails for AI features in a regulated domain
- Experience with products serving emerging markets, where bandwidth, hardware and connectivity are real constraints

WHAT WILL NOT WORK IN THIS ROLE

We would rather be direct about this than waste your time:

- Pure people-management or delivery-management profiles with no recent hands-on coding
- Services and outsourcing backgrounds where the work was scoped, delivered and closed
- Engineers who have only worked on greenfield builds and have never inherited, stabilised and improved a large live codebase
- Anyone who needs a fully specified requirement document before starting work
- Engineers who treat AI as a feature to be bolted on later rather than a design constraint from the start
- Anyone whose AI exposure is limited to calling an API once in a side project, or who is sceptical of AI tooling in the development workflow

LOCATION

The role is based in Kolkata and is on-site. We are open to candidates currently in other cities who are genuinely committed to relocating. We are not considering remote arrangements for this position, because the value of the role comes from proximity to the team and to product decisions.

FIRST 18 MONTHS

What good looks like:

- Months 1 to 3: Learn the codebase, the domain and the team. Ship real code. Identify the top 5 technical risks.
- Months 4 to 9: Own delivery for your pod. Fix what you flagged. Establish engineering standards that hold without supervision.
- Months 10 to 18: Expand ownership across more of the platform, shape the architecture roadmap, and grow the team you have built.

Compensation is structured to match that trajectory, with a clear revision as the scope expands.

HOW WE ASSESS

1. Introductory conversation on background and product experience
2. Technical deep dive on a system you have built, including the decisions you regret
3. Hands-on code and architecture exercise using a realistic Easy Clinic problem
4. AI design round: you will be given a clinical workflow and asked to decide what belongs in a rule, what belongs in a model call, and what it costs at scale
5. Team leadership and hiring discussion
6. Conversation with the Founder on product direction and the growth path

TO APPLY

Send your CV along with a short note covering:

- One product you owned, and how it changed over the time you owned it
- One architecture decision you made that turned out to be wrong, and what you did about it
- One AI feature you have shipped, or one place in a clinical or operational workflow where you would put AI and why
- Your current location and relocation position

📌 Software Engineering Team Lead - Kolkata - Full Stack .NET (Kolkata Metropolitan Area)
🏢 Easy Clinic
📍 Kolkata Metropolitan Area